Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-26T10:20:47.299Z Has data issue: false hasContentIssue false
  • English
  • Français

The recency ratio as predictor of early MCI

Published online by Cambridge University Press:  18 April 2018

Davide Bruno ,
Rebecca L. Koscik ,
John L. Woodard ,
Nunzio Pomara  and
Sterling C. Johnson
Davide Bruno*
Affiliation:
School of Natural Science and Psychology, Liverpool John Moores University, Liverpool, UK; Department of Psychology, Liverpool Hope University, Liverpool, UK
Rebecca L. Koscik
Affiliation:
Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
John L. Woodard
Affiliation:
Department of Psychology, Wayne State University, Detroit, Michigan, USA
Nunzio Pomara
Affiliation:
Nathan Kline Institute for Psychiatric Research, Orangeburg, New York, USA; Department of Psychiatry, School of Medicine, New York University, New York City, New York, USA Department of Psychiatry, School of Medicine, New York University, New York City, New York, USA
Sterling C. Johnson
Affiliation:
Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, Wisconsin, USA Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
*
Correspondence should be addressed to: Davide Bruno, Ph.D., School of Natural Science and Psychology, Liverpool John Moores University Liverpool, UK. Phone: +44 (0)151 904 6320. Email: d.bruno@ljmu.ac.uk.
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives:

Individuals with Alzheimer's disease (AD) present poor immediate primacy recall accompanied by intact or exaggerated recency, which then tends to decline after a delay. Bruno et al. (Journal of Clinical and Experimental Neuropsychology, Vol. 38, 2016, pp. 967–973) have shown that higher ratio scores between immediate and delayed recency (i.e. the recency ratio; Rr) are associated with cognitive decline in high-functioning older individuals. We tested whether Rr predicted conversion to early mild cognitive impairment (early MCI) from a cognitively healthy baseline.

Design:

Data were analyzed longitudinally with binomial regression. Baseline scores were used to predict conversion to early MCI after approximately nine years. Setting: Data were collected at the Wisconsin Registry of Alzheimer's Prevention, in Madison, Wisconsin.

Participants:

For the study, 427 individuals were included in the analysis; all participants were 50 years of age or older and cognitively intact at baseline, and were native English speakers.

Measurements:

Memory data were collected using the Rey's Auditory Verbal Learning Test, and the early MCI diagnosis was obtained via consensus conference.

Results:

Our results showed that higher Rr scores are correlated with greater risk of later early MCI diagnosis, and this association is independent of total recall performance.

Conclusions:

Rr is an emerging cognitive marker of cognitive decline.

Keywords

Alzheimer's diseaserecency ratioserial positionearly MCI
Type
Original Research Article
Information
International Psychogeriatrics , Volume 30 , Issue 12: Issue Theme: Positive Psychiatry , December 2018 , pp. 1883 - 1888
Copyright
Copyright © International Psychogeriatric Association 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bruno, D. et al. (2015). A study on the specificity of the association between hippocampal volume and delayed primacy performance in cognitively intact elderly individuals. Neuropsychologia, 69, 1–8.Google Scholar
Bruno, D. et al. (2017). The recency ratio is associated with reduced CSF glutamate in late-life depression. Neurobiology of Learning and Memory, 141, 14–18.Google Scholar
Bruno, D., Reichert, C. and Pomara, N. (2016). The recency ratio as an index of cognitive performance and decline in elderly individuals. Journal of Clinical and Experimental Neuropsychology, 38, 967–973.Google Scholar
Bruno, D., Reiss, P. T., Petkova, E., Sidtis, J. J. and Pomara, N. (2013). Decreased recall of primacy words predicts cognitive decline. Archives of Clinical Neuropsychology, 28, 95–103.Google Scholar
Carlesimo, G. A., Sabbadini, M., Fadda, L. and Caltagirone, C. (1995). Different components in word-list forgetting of pure amnesics, degenerative demented and healthy subjects. Cortex, 31, 735–745.Google Scholar
Clark, L. R. et al. (2016). Mild cognitive impairment in late middle age in the Wisconsin Registry for Alzheimer's Prevention (WRAP) study: prevalence and characteristics using robust and standard neuropsychological normative data. Archives of Clinical Neuropsychology, 31, 675–688.Google Scholar
Dowling, N. M., Hermann, B., La Rue, A. and Sager, M. A. (2010). Latent structure and factorial invariance of a neuropsychological test battery for the study of preclinical Alzheimer's disease. Neuropsychology, 24, 742.Google Scholar
Engelman, C. D. et al. (2013). Interaction between two cholesterol metabolism genes influences memory: findings from the Wisconsin registry for Alzheimer's Prevention. Journal of Alzheimer's Disease, 36, 749–757.Google Scholar
Foldi, N. S., Brickman, A. M., Schaefer, L. A. and Knutelska, M. E. (2003). Distinct serial position profiles and neuropsychological measures differentiate late life depression from normal aging and Alzheimer's disease. Psychiatry Research, 120, 71–84.Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Koscik, R. L. et al. (2014). Emergence of mild cognitive impairment in late middle-aged adults in the Wisconsin registry for Alzheimer's prevention. Dementia and Geriatric Cognitive Disorders, 38, 16–30.Google Scholar
Koscik, R. L. et al. (2016). Intraindividual cognitive variability in middle age predicts cognitive impairment 8–10 years later: results from the Wisconsin registry for Alzheimer's prevention. Journal of the International Neuropsychological Society, 22, 1016–1025.Google Scholar
Murdock, B. B. (1962). The serial position effect of free recall. Journal of Experimental Psychology, 64, 482–488.Google Scholar
Petersen, R. C. et al. (2010). Alzheimer's disease Neuroimaging Initiative (ADNI) clinical characterization. Neurology, 74(3), 201–209.Google Scholar
R Core Team (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: https://www.R-project.org/Google Scholar
Sager, M. A., Hermann, B. and La Rue, A. (2005). Middle-aged children of persons with Alzheimer's disease: APOE genotypes and cognitive function in the Wisconsin registry for Alzheimer's prevention. Journal of Geriatric Psychiatry and Neurology, 18, 245–249.Google Scholar